How do you evaluate a multi-agent system?

Evaluate each agent against its own role contract, then evaluate the system end to end as a separate suite. Most multi-agent failures are handoff failures rather than reasoning failures, so a system that scores well agent-by-agent can still fail in composition. You need both views to locate a regression.

Give every agent an explicit role boundary — what it owns, what it may call, what it must escalate — and write per-agent evals against that contract. When the end-to-end score drops, the per-agent scores tell you which boundary leaked.

Instrument the handoffs themselves. Record every message crossing between agents so a failed run can be replayed step by step; without that trace, debugging a multi-agent system is guesswork.

In the compliance co-analyst we are building for a UK regulated-firm platform, each agent has one job — gather evidence, follow the procedure, recommend — and a person approves anything reportable. Those explicit boundaries are what make the system testable at all.

Written by Binary AI Labs · Reviewed 2026-11-01